{"id":"W2140353984","doi":"10.1109/wocn.2005.1436038","title":"Replica update strategies in mobile ad hoc networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Replica; Mobile ad hoc network; Computer network; Unavailability; Wireless ad hoc network; Distributed computing; Scalability; Overhead (engineering); Node (physics); Consistency (knowledge bases); Vehicular ad hoc network; Network topology; Mobile computing; Data consistency; Consistency model; Eventual consistency; Engineering; Database; Wireless; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001447767,0.0005652205,0.0008084352,0.0009676089,0.0006770032,0.0009545739,0.001657956,0.0008074116,0.0008923991],"category_scores_gemma":[0.00618297,0.0003058145,0.0002638731,0.0009839643,0.0006338433,0.001882813,0.0007297964,0.0004658541,0.0003196214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004269478,"about_ca_system_score_gemma":0.0003620443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001160035,"about_ca_topic_score_gemma":0.00102926,"domain_scores_codex":[0.9992692,0.0003051107,0.00005583144,0.00008121102,0.0002405896,0.00004799989],"domain_scores_gemma":[0.9970421,0.001536997,0.0002703251,0.000598949,0.0004520061,0.00009961333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004773035,0.0002114351,0.003162619,0.0004299722,0.0001593628,0.0009669357,0.001051835,0.4275425,0.02422658,0.06152343,0.004612214,0.4756358],"study_design_scores_gemma":[0.0001129539,0.0002893041,0.0004238619,0.00003359571,0.00007063651,0.0005640764,0.000199862,0.949721,0.006344982,0.03318145,0.009023256,0.00003500565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07927801,0.007249562,0.9051282,0.0004087347,0.0002819744,0.0002806105,0.00005420572,0.001033908,0.006284755],"genre_scores_gemma":[0.867155,0.002160283,0.1265477,0.000106059,0.0001699054,0.0002074685,0.00007752603,0.00006492422,0.0035112],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001657956,"threshold_uncertainty_score":0.007656634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01219715689172357,"score_gpt":0.2464666841521998,"score_spread":0.2342695272604762,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}